Motivation: Determining whether a trait and phylogeny share some degree of phylogenetic signal is a flagship goal in evolutionary biology. Signatures of phylogenetic signal can assist the resolution of a broad range of evolutionary questions regarding the tempo and mode of phenotypic evolution. However, despite the considerable number of strategies to measure it, few and limited approaches exist for categorical traits. Here, we used the concept of Shannon entropy and propose the delta statistic for evaluating the degree of phylogenetic signal between a phylogeny and categorical traits. Results: We validated delta as a measure of phylogenetic signal: the higher the delta-value the higher the degree of phylogenetic signal between a given tree and a trait. Based on simulated data we proposed a threshold-based classification test to pinpoint cases of phylogenetic signal. The assessment of the test's specificity and sensitivity suggested that the delta approach should only be applied to 20 or more species. We have further tested the performance of delta in scenarios of branch length and topology uncertainty, unbiased and biased trait evolution and trait saturation. Our results showed that delta may be applied in a wide range of phylogenetic contexts. Finally, we investigated our method in 14 360 mammalian gene trees and found that olfactory receptor genes are significantly associated with the mammalian activity patterns, a result that is congruent with expectations and experiments from the literature. Our application shows that delta can successfully detect molecular signatures of phenotypic evolution. We conclude that delta represents a useful measure of phylogenetic signal since many phenotypes can only be measured in categories.
Year of publication: 2019